Python Lesson 5 | BehindTheBall

In this lesson, the instructor teaches how to save scraped NBA player stats into a CSV file using Python. The CSV format helps organize the data into rows and columns, so it’s easy to use later in tools like Excel, R, or pandas.

The video walks through how to:

Open a CSV file in write ('w') or append ('a') mode,
Loop through player data and separate values with commas (to make columns),
Write all players to the file, with each one on a new row.

open('file.csv', 'w') vs. open('file.csv', 'a'):
- 'w' (write mode) erases everything and starts fresh.
- 'a' (append mode) adds new data without deleting the old.
Commas = Columns:
- Commas separate values into different columns in a CSV file.
- Example: "Kobe Brown, SF" puts "Kobe Brown" in one column and "SF" in another.
New rows for each player:
- After writing a player's stats, the code adds a new line (\n) to move to the next row.
.rstrip() is used to remove hidden new line characters that would otherwise mess up the file formatting.
Data is saved in a clean, usable format, and the resulting CSV file can be opened later for analysis.

Data Scraping: Lesson 5

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